Sierra Nevada Fraction Analysis

Load data

Internal

CN

Read raw

Templates

Merge raw w/ template

14C

Mass

Call:
lm(formula = loss_pct ~ PM + ECO, data = sra.frc.mss.lss.df[-which(sra.frc.mss.lss.df$Probe == 
    "BSpp_comp_2001_18-28"), ])

Residuals:
    Min      1Q  Median      3Q     Max 
-4.1953 -0.9261 -0.4445  0.7965  5.7767 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   4.8136     0.5726   8.406 1.06e-10 ***
PMBS         -0.1405     0.6486  -0.217 0.829539    
PMGR         -2.3959     0.6382  -3.754 0.000507 ***
ECOwf        -1.0117     0.6382  -1.585 0.120098    
ECOrf        -1.7850     0.6394  -2.792 0.007729 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.831 on 44 degrees of freedom
Multiple R-squared:  0.3641,    Adjusted R-squared:  0.3063 
F-statistic: 6.299 on 4 and 44 DF,  p-value: 0.0004255

Interestingly, it appears that AN soils have proportionally LESS minC by mass than do GR or BS soils, significantly so at depth. Why would this be? Possibly because AN soils have higher losses (DOC) during fractionation?

External data

Atmosphere

from C. Rasmussen (’01 C, N; ’09 14C, frc mass, C, N)

calculating Δ14C from fraction modern

Analysis

Misc. functions

Bulk C

2001

2009

2019

Fraction C

C, CN profiles

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C distribution

`summarise()` has grouped output by 'PMeco'. You can override using the `.groups` argument.

Fraction 14C

Depth profiles

Spline ’01, ’09

Spline C

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Spline 14C

C-weighted 14C spline

14C time series

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$`20`

$`30`

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$`20`

$`30`

Char pool calc

Free light vs respired 14C

Thermal fractions

C release (thermograms)

Thermal fraction 14C